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Alex Inch

@alexinch.bsky.social

Interested in open-ended machine learning and agentic systems. Studying a DPhil on world models at Oxford Robotics.

23 Followers  |  426 Following  |  10 Posts  |  Joined: 06.11.2023  |  1.7211

Latest posts by alexinch.bsky.social on Bluesky

The Financial Consequences of Legalized Sports Gambling <div> <div> Following a 2018 ruling of the U.S. Supreme Court, 38 states have legalized sports gambling. We study how this policy has impacted consumer finan

This paper looking at financial impacts is damning, incl. an estimated 28% rise in bankruptcies for states which legalised sports gambling papers.ssrn.com/sol3/papers....

31.10.2025 23:31 β€” πŸ‘ 5    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

That 500ml estimate is one of a few. Mistral estimated 10ml for 100 tokens, Google said median 0.3ml per-prompt: the 17B for the US is still only a fraction of a percent of your national water use. Why focus on water when electricity use is orders of magnitude more significant?

31.10.2025 23:27 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

You're conflating two things. The emissions/electricity impact is real and significant. Water use is irrelevant. 17B gallons sounds like a lot, but global water use last year was 4.3 trillion cubic metres, around 10^15 US gallons.

31.10.2025 13:12 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

Hi Hendrik, is there an archive of these visualisations? I'd love to compare eg. ICML 2024 vs 2025, either via the viewer or raw data if it's available.

15.07.2025 03:36 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

It's interesting that this is a fairly local take. Stanford reported that 36% of US citizens are optimistic about AI vs 83% in China. BlueSky broadly has an anti-AI sentiment, but that doesn't reflect global attitudes.

27.04.2025 01:00 β€” πŸ‘ 8    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

On the other hand, Deepmind and Google are working on a much wider range of scientific problems that would benefit from powerful AI than their competitors.

03.04.2025 23:59 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Imo it's a consequence of how hard it is to measure task performance - benchmarks give you a very narrow view of performance.

10.03.2025 17:10 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

I think the o1 direction is an interesting result of this. Fields with easy verification are simple fit for plugging in traditional RL. How do you verify a good suggestion for writing feedback?

10.12.2024 17:50 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

If only there was more PRS on Spotify!

04.12.2024 15:10 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

Looks a bit like the reasoning traces out of r1/QwQ

04.12.2024 00:01 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

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